AI for plants, utilities and industrial operations — predictive maintenance, vision-based quality inspection, process and energy optimisation, and digital twins — built on your machine data and deployed safely alongside your control systems.
Your machines already signal when they are going to fail, where defects come from and where the energy goes. Industrial AI turns those signals into a work order, a set-point or an alert, early enough to act on.
We bring AI to the plant floor: production lines, process plants, utilities and the equipment that keeps them running. We connect to what is already there — PLCs, SCADA, historians and MES — through OPC UA, MQTT and Modbus, and retrofit sensors where the data does not yet exist. Models run at the edge, next to the machines, so decisions are made in milliseconds and keep running if the network drops.
Operational technology is not IT, and we treat it accordingly. Connections are read-only by default, networks are segmented in line with IEC 62443 practice, and nothing writes back to a control system without an operator approving it. Results land where your teams already work: a work order in the CMMS, an alert to the shift lead, a recommendation on the operator’s screen.
We start with one line or one class of asset, agree a baseline — downtime, scrap, OEE, energy per unit — and prove the improvement against it before scaling across the plant.
Machine, sensor and historian data collected securely over OPC UA, MQTT or Modbus.
Models trained on your equipment’s own history and validated against a measured baseline.
Inference runs next to the line: real-time, and still working when the link drops.
Work orders, alerts and set-point recommendations go to the people who decide.
Vibration, temperature, current and acoustic data used to forecast bearing, motor, pump and gearbox failures days or weeks ahead, and to plan the repair before the breakdown.
Computer vision on the line that catches surface defects, missing parts, misprints and fill levels at full speed, and records every rejected item with its image.
Models that find the settings behind good batches and recommend set-points that cut scrap, rework and variation.
Energy use tracked per machine, line and unit produced, with peak-load forecasting and savings in compressed air, HVAC and furnaces.
A live model of assets, lines and process flow for monitoring, what-if simulation and testing changes before they reach the plant.
Models on industrial edge hardware next to the machines, for low latency, local data and operation through network outages.
PLCs, SCADA, historians, MES and ERP connected into one governed data platform, without disturbing the control layer.
Wireless vibration, temperature, power and environmental sensors added to older machines that have no data to give.
Technicians ask questions in plain language and get answers from manuals, procedures and maintenance history, with fault-finding steps attached.
Vision that flags missing PPE, people in exclusion zones and unsafe acts, with alerts to supervisors and a record for review.
Availability, performance and quality per line and shift, with the reasons behind every loss captured automatically.
Segmented networks, read-only connections and approval before any write-back, in line with IEC 62443 practice.
An alert that arrives after the breakdown is just a report. We build for the warning that comes early enough to plan the repair.